Workforce Development

AI Development Track   

The AI Development Track is a hands-on journey that takes students from Python fundamentals all the way to becoming a professional AI Engineer. Over three intensive courses, you'll master the complete AI development lifecycle and have a portfolio of production-ready applications. This program is designed for those ready to move beyond using AI to building the intelligent applications of tomorrow.  

Cloud‑Native Application Deployment 

Course 2 of 3. 

Turn your AI ideas into real, cloud‑powered applications. Learn how modern AI-backed web apps are built and shipped. You’ll transform a Python script into a full-stack web application with Flask, SQLAlchemy, and a hand‑coded front end—and then take it all the way to the cloud. Containerize with Docker, automate with GitLab CI/CD, and deploy to Kubernetes. By the end, your work isn’t just running locally… it’s live. Ideal for Python developers looking to transition into web development or backend engineering. IT professionals who want to modernize their skillset with containerization and orchestration technologies like Docker and Kubernetes. Graduates of Course 1 who want to see their code come to life as a live, interactive web application. Aspiring DevOps engineers seeking a practical, project-based introduction to CI/CD pipelines. 

Prerequisite Skills  

This course focuses on web technologies and cloud infrastructure. To ensure success, students should have: 

Python Proficiency: A solid understanding of Python syntax, functions, and Object-Oriented Programming (OOP), as covered in Course 1: Python AI Fundamentals

Command-Line Literacy: Comfort with navigating the file system, running scripts, and managing files via a terminal. 

Git Fundamentals: Understanding of basic version control concepts like cloning, committing, and pushing code. 

Logical Thinking: The ability to understand how data flows between a client (browser), a server (API), and a database. 

Additional Courses in AI Development Track:

1: Python AI Fundamentals: 6/8/26 – 8/30/26

3: Applied AI, Agents & Automation  7/20/26 - 10/18/26 or 11/23/26 - 2/21/21